{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "def draw_loss(filepath):\n",
    "    import matplotlib.pyplot as plt\n",
    "    loss_list = list(np.load(filepath))\n",
    "    plt.plot(list(range(1, len(loss_list) + 1)), loss_list)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "draw_loss('/home/yinzp/gitee/paper-reading/DFND/cache/teacher/teacher_loss_120.npy')"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
 ],
 "metadata": {
  "orig_nbformat": 4,
  "language_info": {
   "name": "python",
   "version": "3.6.9",
   "mimetype": "text/x-python",
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "pygments_lexer": "ipython3",
   "nbconvert_exporter": "python",
   "file_extension": ".py"
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.6.9 64-bit"
  },
  "interpreter": {
   "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}